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| Section | Objectives |
|---|---|
| Topic 1: Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Topic 2: Develop containerized solutions on Azure | - Implement containerized applications
|
| Topic 3: Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
| Topic 4: Connect to and consume Azure services | - Integrate Azure services
|
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NEW QUESTION # 63
You have two Azure Container Registry (ACR) instances: ACR01 and ACR02.
You plan to implement a containerized application named APP1 that will use a base image named BASE1.
The image for APP1 will be stored in ACR01. The image BASE1 will be stored in ACR02.
You need to automate the planned implementation by using a sequence of five Azure command-line interface (Azure CLI) commands. Your solution must ensure that the APP1 image stored in ACR01 will be automatically updated when the BASE1 image is updated.
In which order should you arrange the commands to develop the solution? To answer, move all commands from the list of commands to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Answer:
Explanation:
Explanation:
NEW QUESTION # 64
You need to secure an Azure OpenAI resource so that it is only reachable from your virtual network and not from the public internet. What should you configure?
Answer: C
Explanation:
Private Link/private endpoints assign the Azure OpenAI resource a private IP within your VNet and allow disabling public network access, ensuring traffic stays on the Microsoft backbone network and isn't reachable from the public internet.
NEW QUESTION # 65
Drag and Drop Question
You are deploying an Azure Function app that retrieves secrets from Key Vault by using a managed identity.
The deployment must ensure that identity and secret configuration are in place before the function code is deployed.
You need to deploy the function app securely.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Step 1: Create the function app
You must first provision the underlying Azure Functions infrastructure before you can bind an identity or configuration settings to it.
Step 2: Assign a managed identity to the function app
Turning on the managed identity (such as a system-assigned identity) creates a distinct security principal in Microsoft Entra ID for the resource.
Step 3: Grant access to Key Vault
Use the managed identity's principal ID to create an access policy or RBAC role assignment in Key Vault, allowing the app to read secrets.
Step 4: Add Key Vault references to application settings.
Configure the Function App's application settings to point to the Key Vault secret URIs (@Microsoft.KeyVault(...)), which can now be securely resolved by the identity.
Step 5: Deploy the function code
Finally, deploy the application code. This ensures that when the code initializes and executes, all environment variables and secrets are already active and accessible, preventing application startup failures.
Reference:
https://learn.microsoft.com/en-us/azure/app-service/app-service-key-vault-references
NEW QUESTION # 66
Hotspot Question
You are using Python SDK to develop a containerized AI application that retrieves the value of a runtime setting stored in an Azure App Configuration resource. The application will run in Azure in the security context of a managed identity.
The application must work in a local development environment without any code changes.
You need to complete the code that implements the retrieval.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: DefaultAzureCredential
This class from the azure-identity library provides an automated, sequenced token authentication flow. When running locally, it automatically falls back to your local development environment credentials (such as Azure CLI, environment variables, or VS Code login). Once deployed to Azure, it seamlessly switches to the environment's managed identity without requiring any code changes.
Box 2: get_configuration_setting
This method belongs to the AppConfigurationClient in the azure-appconfiguration SDK. It is used to fetch a specific configuration key-value pair using its key name ("FeatureX") and an optional label.
Reference:
https://learn.microsoft.com/en-us/azure/developer/python/tutorial-containerize-deploy-python-web-app-azure-04
NEW QUESTION # 67
Case Study 2 - Proseware Inc.
Background
Proseware Inc. develops AI-powered knowledge management solutions for enterprise customers.
The company is modernizing its platform to support semantic search, intelligent document retrieval, and real-time partner integrations.
The engineering team uses Python and Azure SDKs. The architecture is being redesigned to support containerized microservices, vector search workloads, and serverless backend processing.
Planned Application Architecture
Microservices are containerized by using Docker.
Code for containerized microservices and Azure Function apps is developed locally but stored in a GitHub repository.
Custom images for containerized microservices are stored in Azure Container Registry (ACR).
Base images are stored in Docker Hub. Custom images must be rebuilt automatically whenever their base images are updated.
Azure Cosmos DB for NoSQL stores documents, metadata, and vector embeddings.
Azure Functions generate vector embeddings of Azure Cosmos DB for NoSQL-hosted documents and send messages to Service Bus to trigger search index updates.
Azure Container Apps (ACA) apps host backend API services that provide semantic search across Azure Cosmos DB for NoSQL documents. API services process Service Bus messages and update search indexes.
Azure Kubernetes Service (AKS) processes batch vector embedding regeneration for existing Azure Cosmos DB for NoSQL documents (whenever the embedding model is changed).
An extranet-facing containerized webhook allows business partners to submit documents to be processed by internal AI workflows for semantic search and retrieval.
Monitoring
Telemetry generated by Azure resources is sent to Azure Monitor.
A Log Analytics workspace is used to collect ACA apps logs, AKS container logs, and Azure Functions apps logs.
Monitoring of Azure Functions is currently implemented by using Azure Application Insights SDK instrumentation.
Business Requirements
Embeddings for new or updated Azure Cosmos DB for NoSQL-hosted documents must be automatically generated.
Backend API services must scale automatically during business hours.
Cold start delay of backend APIs must be minimized.
Secrets must be stored outside of container images.
Developers must be able to correlate telemetry across Azure Functions hosts and apps.
All tracing must be implemented by using OpenTelemetry SDK instrumentation.
Development efforts must be minimized.
Technical Requirements
Container images must be built automatically and validated before code updates are merged into the main branch.
Image build automation must run inside the Azure Container Registry, eliminating dependency on local developer machines and external build services.
Dependency of image builds on local developer machines must be eliminated.
Event-driven scaling in ACA must occur based on the number of pending messages in the Azure Service Bus queue.
Azure Cosmos DB for NoSQL RU consumption must be minimized.
Vector similarity search must use embeddings stored in Azure Cosmos DB for NoSQL.
The partner-facing containerized webhook service must run on Azure App Service.
Secrets must NOT be stored in container images, source control, or application configuration directly. They must be accessed securely at runtime.
All secrets must be stored centrally in Azure Key Vault and accessed at runtime through a managed identity.
Azure App Service must supply secrets at runtime without relying on external services.
Resources and workloads must be deployed by using Bicep templates through an automated, version-controlled pipeline. Local and command-line deployments must be eliminated to ensure repeatable, auditable deployments.
Known Issues
RU consumption spikes during vector similarity queries.
Drag and Drop Question
You need to configure event-driven scaling for the backend API services to meet the technical requirements.
Which settings should you use for each element? To answer, move the appropriate settings to the correct elements. You may use each setting once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Scenario, technical requirements.
Event-driven scaling in ACA must occur based on the number of pending messages in the Azure Service Bus queue.
Box 1: Azure Service Bus
Scaler TypeType
Set the scale rule type to custom.
KEDA Scaler Name: Set the type inside the custom specification block to azure-service-bus.
Box 2: messageCount
Trigger Metadata Values
The metadata block dictates how KEDA calculates the required replica count.
Configure the following core metadata parameters:
queueName: The explicit string name of your targeted Azure Service Bus
*-> queue.messageCount: The target integer threshold of concurrent pending messages assigned per replica (e.g., 5 or 10). KEDA uses this value to scale out systematically.
activationMessageCount: Set to 1 or 0. This defines the exact metric floor required to transition the container app out of a dormant state.
namespace: The canonical name of your Service Bus namespace
Box 3: 0
Min-Replicas ConfigurationValue
Set --min-replicas to 0.
Setting this value to zero enables full serverless cost efficiency. KEDA actively handles the background polling, allowing your backend API containers to scale down completely and run zero active replicas when the Service Bus queue contains zero pending messages.
Reference:
https://oneuptime.com/blog/post/2026-02-16-how-to-set-up-keda-based-auto-scaling-with-queue-triggers-in-azure-container-apps/view
NEW QUESTION # 68
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